In recent years, the popularity of systems using wireless radio communication has increased substantially. For example, cellular communication systems and wireless networks have now become commonplace. The increased requirement for frequency spectrum resource has led to an increased desire for efficient communication and especially at higher frequencies and for higher data rates.
For example, Broadband Wireless Access systems (BWA) are becoming common not only in fixed deployments but also in mobile deployments. In order to increase the capacity of such BWAs, it is desirable to increase the data rate of the wireless communication. As a specific example, the Institute of Electrical and Electronic Engineers (IEEE) have formed a committee for standardizing an advanced air interface for operation in licensed bands known as IEEE 802.16m. (Trademark). The 802.16m™ standard comprises BWA Medium Access Control (MAC) and Physical Layer (PHY) specifications aimed at enhancing BWAs to meet the cellular layer requirements of International Telecommunications Union Radiocommunications Sector (IMT-Advanced) next generation mobile networks. Similarly, Wireless Local Area Network WLANs are becoming common not only in business environments but also in domestic environments. The IEEE has formed a committee for standardizing a very high-speed WLAN standard known as IEEE 802.11vht. It is intended that the 802.11vht™ standard will help WLANs meet the expanding bandwidth needs of enterprise and home networks, as well as those of WLAN hot spots. Other popular examples of wireless networks include the more popular names of WiFi™ and WiMAX™ (corresponding to IEEE 802.11n and IEEE 802.16e)
In order to achieve high data rates over the air interface, a number of advanced radio techniques are employed. It has been found that in systems using open-loop approaches (i.e. without the transmitter using knowledge of the transmit channel or the signal received at the receiver) significant improvement can be achieved by using multiple antennas at the transmitter and the receiver. In particular, many radio communication systems, such as WLANs, provide for a plurality of transmit and receive antennas to be used. Specifically, some transmission techniques involve transmitting a data stream by simultaneously transmitting different signals derived from the data stream from different antennas over the same communication channel. The receiver(s) of these techniques typically also comprise a plurality of antennas each of which receive a combined signal corresponding to the transmitted signals modified by the individual propagation characteristics of the radio link between the individual antennas. The receiver may then retrieve the transmitted data stream by evaluating the received combined signal.
Such techniques may also be used in closed loop configurations wherein the receiver may communicate information back to the transmitter allowing this to weight the signals to the individual antennas. Specifically, data may be fed back to the transmitter to allow this to provide a suitable beamforming. Such open and closed loop techniques are known as Multiple Transmit Multiple Receive (MTMR) or Multiple Input Multiple Output (MIMO) schemes and can be designed to derive benefit from spatial diversity between the antennas in order to improve detection. Indeed, the equivalent Signal to Noise Ratio (SNR) of the combined signal is typically increased compared to the single antenna case thereby allowing higher channel symbol rates or higher order constellations. This may increase the data rate for the communication link and thus the capacity of the communication system.
In order to further enhance the capacity of MIMO systems, it has been proposed that multiple users may share the same air interface resource, and specifically that two users may be allocated the same time-frequency block. For example, two user equipments may be allowed to simultaneously transmit uplink signals to a base station using the same frequency channel.
In such systems, the scheduling of user equipments (i.e. the assignment of time-frequency resources to user equipments) is critical for the performance of the system, and in particular it is of the utmost importance that the most suitable user equipments are scheduled to share the same time-frequency resource block.
In known systems, such scheduling may be based on the overall channel conditions or the transmit beamforming of the transmitting MIMO user equipments (the weights applied to each MIMO antenna of the transmitting MIMO user equipment). Specifically, typical scheduling algorithms seek to allocate user equipments to share time-frequency resource blocks such that the sharing user equipments have the most different overall channel conditions or transmit beamforming characteristics.
However, although such scheduling may provide acceptable performance in many scenarios, it also tends to be suboptimal and have a number of disadvantages. For example, in many scenarios it may result in complex processing e.g. in order to determine the overall channel responses and to evaluate which user equipments have overall channel responses that are most suitable for sharing resource blocks. Furthermore, in order to provide the desired performance and differentiation between the user equipments sharing the same time-frequency resource block, complex equalization is typically necessary by the individual receivers. For example, as the scheduling is based on transmitter or overall channel conditions, the receiver equalization will typically need to utilize complex non-linear equalization in order to reduce the cross-interference between the sharing user equipments sufficiently.
Such non-linear equalization may for example include an iterative equalization wherein received data symbols are estimated in each iteration, with the estimated data symbols of one user equipment of a previous iteration being used to estimate the data symbols of the other user equipment in the following iteration. This equalization process will typically have to be iterated a number of times resulting in high computational requirements. Hence, an improved communication system would be advantageous and in particular a system allowing increased flexibility, facilitated implementation, reduced complexity, reduced resource usage, increased spectral efficiency, improved and/or facilitated multi-user operation and/or improved performance would be advantageous.